Triple
T9248536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyoto Basin |
E222258
|
entity |
| Predicate | formsGeographicSettingFor |
P3227
|
FINISHED |
| Object | Muko |
E129411
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Muko | Statement: [Kyoto Basin, formsGeographicSettingFor, Muko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Muko Context triple: [Kyoto Basin, formsGeographicSettingFor, Muko]
-
A.
Muko
chosen
Muko is a small city in Japan’s Kyoto Prefecture, known for its residential character and proximity to Kyoto City.
-
B.
Moudon
Moudon is a historic town and former district capital in the canton of Vaud, Switzerland, known for its medieval old town and location in the Broye valley.
-
C.
Kokemäki
Kokemäki is a small town and municipality in the Satakunta region of western Finland, known for its location along the Kokemäenjoki River and its historical roots dating back to medieval times.
-
D.
Laakso
Laakso is a residential district in Helsinki, Finland, known for its green areas and proximity to central neighborhoods like Meilahti.
-
E.
Nayki
Nayki is an island located within Lake Rakshastal in the Tibet Autonomous Region of China.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca841d2b18819089f9faf5b2c2aec0 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd05f6d62c8190a1e33f1854767b47 |
completed | April 1, 2026, 11:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d077fed7888190a5d36bc2ee4c2bd2 |
completed | April 4, 2026, 2:31 a.m. |
Created at: March 30, 2026, 7:31 p.m.